1. Field of the Invention
The present invention relates to analog-to-digital converters, and in particular, to a structure for adaptive sigma-delta modulation with improved dynamic range.
2. Description of the Related Art
(Note: This application references a number of different publications as indicated throughout the specification by reference numbers enclosed in brackets, e.g., [x]. A list of these different publications ordered according to these reference numbers can be found below in the Section entitled “Publications” in the Detailed Description of the Preferred Embodiment. Each of these publications is incorporated by reference herein.)
Analog-to-digital converters (ADCs) nowadays use an innovative technology known as sigma-delta modulation (SDM) to perform the conversion process. Sigma-delta modulators/demodulators are known to provide a high-resolution digital representation of analog signals. Moreover, sigma-delta modulators/demodulators show high robustness to circuit imperfections, which makes them attractive for low-cost and reliable implementations. Sigma-delta modulation achieves high resolution data conversion via noise shaping. Current sigma-delta modulators/demodulators can provide up to 20+ bits of resolution.
FIGS. 1A and 1B illustrate a modulator 10 and demodulator 12 of a single-loop prior art implementation of sigma-delta modulation. In this example, the modulator 10 is comprised of a summing junction 14, noise shaping filter 16, and single-bit quantizer 18, while the demodulator 12 is comprised of a low-pass filter 20. Other implementations may include multi-loop, multi-stage, and multi-bit structures.
In the modulator 10, a sampled analog input signal x(n) is compared with the output of the modulator y(n). The comparison error is filtered at the filter 16 and then converted into a binary output signal y(n) having a specified number of bits at the quantizer 18. The binary output signal y(n) is a representation of the analog input signal x(n) contaminated with noise created by the quantizer 18. The low-pass filter 20 in the demodulator 12 filters out a shaped quantization signal from the binary output signal y(n), thereby resulting in a good approximation ({circumflex over (x)}(n)) of the analog input signal x(n).
In sigma-delta modulation, the signal-to-noise ratio (SNR) decreases linearly with the amplitude of the input signal. The dynamic range of the modulator 10 is a measure of how much the amplitude of the input signal can be reduced before the SNR becomes unity. A typical dynamic range for sigma-delta modulation is from 70 to 150 dB.
Adaptive sigma-delta modulation (ASDM) increases the dynamic range of sigma-delta modulation by scaling either the input signal or the step-size of the quantizer through an estimation of the input signal strength. This estimate can be made from the input signal itself or from the modulator output.
FIGS. 2A–D illustrate prior art adaptation schemes using input and output information, wherein FIGS. 2A and 2B show input scaling using an input strength estimation 22 at a multiplier 24, while FIGS. 2C and 2D show quantizer step-size scaling using an input strength estimation 22 that controls the quantizer 18. Using the input signal to perform the estimation is known as forward estimation, while using the output signal is known as backward estimation.
Adaptation could be done continuously or sporadically in time. Moreover, the value of the scaling signal d(n) could be continuous in amplitude or restricted to a specific range of values.
Several adaptation techniques have been investigated in the literature [2–6]. Chakravarthy [2] proposed an adaptive scheme that is based on averaging the number of transitions at the modulator output. Jaggi and Chakravarthy [3] used a digital-to-analog converter to instantaneously control the feedback pulse amplitude. Yu et. al. [4] developed a technique based on estimating the maximum input amplitude over a certain interval and using it to adapt the quantization step-size. This work has been extended by Dunn and Sandler [5] to a multi-bit quantizer, while Ramesh and Chao [6] implemented a backward adaptation.
Some the limitations of these techniques include: (1) stability is not guaranteed; (2) they still provide limited dynamic range; and (3) most of these techniques involve complicated logic. Consequently, there is a still a need in the art for improved techniques for adaptive sigma-delta modulation.